Kaala 2.0: Scalable IoT/NextG System Simulator

The IoT world is evolving with the latest technology trends, like edge computing, augmented & virtual reality, machine learning, robotics, and 5G. With the digital transformation happening in Industry 4.0, many industries are moving toward private 5G networks. There are massive number (hundreds to thousands) of IoT devices in a single factory depending on the scale of the industry and these factories consists of critical IoT devices, like fire or gas sensors which need to operate reliably with less latency. To efficiently realize the capabilities, such as ultra reliable low latency communications (URLLC), enhanced mobile broadband (eMBB), and massive machine-type communications (mMTC) offered by 5G, the next generation IoT devices/applications need a paradigm shift in their design and need to be evaluated under simulation using 5G networks before getting deployed in the real-world. However, many IoT simulators run in isolation and do not interface with real-world IoT cloud systems or support 5G networks. This isolation makes it difficult to design, develop and evaluate IoT applications for industrial automation systems and for experiments to fully replicate the diversity that exists in end-to-end, real-world systems using 5G networks. Kaala 2.0 is the first scalable, hybrid, end-to-end IoT and NextG system simulator that can integrate with real-world IoT cloud services through simulated or real-world 5G networks. Kaala 2.0 is intended to bridge the gap between IoT simulation experiments and the real world using 5G networks. The simulator can interact with cloud IoT services, such as those offered by Amazon, Microsoft, and Google. Depending on the configuration, Kaala 2.0 supports simulation of User Equipment (UE), 5G Radio Access Network (RAN) and 5G Core and at the same time support real-world User Equipment (UE), 5G Radio Access Network (RAN) and 5G Core. Kaala 2.0 can simulate many diverse IoT devices to evaluate mMTC, simulate events that may simultaneously affect several sensors to evaluate URLLC and finally simulate large amount of data to evaluate eMBB.